DBMS > AnzoGraph DB vs. mSQL vs. RDF4J vs. SAP HANA

System Properties Comparison AnzoGraph DB vs. mSQL vs. RDF4J vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

mSQL (Mini SQL) is a simple and lightweight RDBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

cambridgesemantics.com/anzograph

hughestech.com.au/products/msql

rdf4j.org

www.sap.com/products/hana.html

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

rdf4j.org/documentation

help.sap.com/hana

Developer

Cambridge Semantics

Hughes Technologies

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

SAP

Initial release

2018

1994

2004

2010

Current release

2.3, January 2021

4.4, October 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

free licenses can be provided

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Unix
Windows

Appliance or cloud-service

Data scheme

Schema-free and OWL/RDFS-schema support

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

Supported programming languages

C++
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

yes

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